Centre for Operational Research and Logistics

Events and Seminars

Research Seminar

Optimizing the Core Tensor in Tucker Decomposition: Model and Algorithms

Approximating high order tensors by low Tucker-rank tensors have applications in psychometrics, chemometrics, computer vision, biomedical informatics, among others. Traditionally, solution methods for finding a low Tucker-rank approximation presume that the size of the core tensor is specified in advance, which may not be a realistic assumption in many applications. In this work we propose a new computational model where the configuration and the size of the core become a part of the decisions to be optimized. Our approach is based on the so-called maximum block improvement (MBI) method for non-convex block optimization. Numerical tests on various real data sets from gene expression analysis and image compression are reported, which show promising performances of the proposed algorithms.

Biography: Dr Zhening Li is a Lecturer in the Department of Mathematics and a member of the Centre for Operational Research and Logistics in the University of Portsmouth. He received BSc degree in Mathematics from Peking University in 1999, MA degree in Mathematics and Financial Engineering from York University in 2003, and PhD degree in Systems Engineering and Engineering Management from The Chinese University of Hong Kong in 2011. Zhening's research is at the interface of Operations Research and Mathematics. In particular, he works on theoretical and computational optimization, algorithm design and analysis, with applications in finance, engineering, game theory, etc. His recent research focuses on algorithms and applications of polynomial optimization, theory and computation methods for tensor optimization models.

Speaker

Dr Zhening Li, Department of Mathematics, University of Portsmouth


Venue

Lion Gate Building, LG 2.01


Date and Time

Thu, 2 Oct 2014, 13:00 - 14:00 (BST)


For further information or any enquiries please contact our event co-ordinator, Jana Ries, at corl@port.ac.uk